As the use of information and communication technology (ICT) has evolved or automobiles have become smarter, various vehicle-mounted apparatuses are being made high-functional and multifunctional. In this situation, when a message is received in a vehicle by, for example, a smartphone or a vehicle-mounted apparatus connected to the smartphone through a social networking service (SNS) or another service, the message may be displayed in the vehicle.
If a message is displayed in a situation in which the driving load of the driver, which is a so-called workload, is high, the driver's attention may be diverted to the displayed message and may not concentrate on the driving. As a result, so-called distraction may occur, in which case the driving may be adversely affected.
An information display system described below is disposed as an example of countermeasures against this distraction. In this information display system, information acquired from engine control units (ECUs) intended for vehicle control, a navigation ECU, or the like through an in-vehicle local area network (LAN) is used to execute load deciding processing by which whether the driving load is large or small is decided. For example, if the driver is backing up the vehicle, is turning a corner, is turning to the right or left, is changing the lane, or is accelerating or decelerating the vehicle, the driving load is decided to be large. Alternatively, if the vehicle is traveling on a narrow road, in a school zone, around a curve, is passing through a traffic intersection, a confluence, or a railroad crossing, does not keep a sufficient interval between the vehicle and the preceding vehicle, or is traveling in a congested state or at low visibility, the driving load is also decided to be large.
As an example of technology to measure the driver's load, a calling timing control apparatus is also proposed. This calling timing control apparatus controls a timing at which to originate a call to the driver's telephone or the like by using two workload measurement methods described below.
For example, in one workload measurement method, a quantification model, which is used to obtain a workload from data acquired from a line-of-sight sensor and a vehicle sensor, is created in advance. A workload is calculated by applying the data acquired from the line-of-sight sensor and vehicle sensor to the quantification model. This quantification model is created by using a statistical method such as in linear multi-regression analysis, main component analysis, or factor analysis to obtain, in various situations (such as at traffic intersections and during overtaking and the manipulation of an audio device), relationships between data detected by the line-of-sight sensor and vehicle sensor and the values of workloads in these situations. The values of workload in various situations are determined according to, for example, evaluation values to which the driver evaluates workloads that the driver feels in these situations. The values of workloads are not based on the driver's subjective evaluation, but are determined from the driver's biological signals (such as the heart rate, blood pressure, and breathing speed) that are acquired in various situations.
In the other workload measurement method, a workload conversion table, which is used to convert data acquired by a line-of-sight sensor, a vehicle sensor, and a road attribute analyzing unit, is referenced to convert data acquired by each sensor to workload data. The workload conversion table stores workload data corresponding to driver's manipulations, road attributes, manipulations of devices, acoustic content, and line-of-sight motions. Related techniques are disclosed in, for example, Japanese Laid-open Patent Publication No. 2014-91440, Japanese Laid-open Patent Publication No. 2010-282592, Japanese Laid-open Patent Publication No. 2004-70795, Japanese Laid-open Patent Publication No. 2008-241309, Japanese Laid-open Patent Publication No. 10-244892, and Japanese Laid-open Patent Publication No. 2010-237954.